In current engineering practice, the design and construction of structures such as tunnels, underground sewers, underground parking garages, foundations, buildings, and the like often begin with a characterization of the engineering response of soil due to the proposed construction. A numerical model may be used to predict static and dynamic soil structure reaction to construction activities. Generally, the characterization may include performing laboratory or field testing of the soil, and using the resultant data to develop a numerical model of the soil behavior. The numerical model may then be used to predict soil response to construction activities.
Most soil numerical models include constitutive models to represent soil behavior at the point or “element” level and describe soil stress-strain-strength response. Most constitutive models used in geomechanics are based on the concepts of plasticity. Early forms of a yield criterion include the Tresca and von Mises yield criteria used to represent material failure. These models are useful to establish a general framework for understanding material behavior but do not capture the complex behavior of geologic materials including non-linearity, hardening and softening, anisotropy, and strain rate dependence.
These constitutive models define the material behavior using a fixed set of equations and geometric objects that define the yield surface. An advantage of these types of constitutive relations relates to model generalization. Using a limited set of laboratory tests, a set of hypotheses about the general stress strain behavior of soil, and conservation laws of mechanics, the model clearly defines stress strain behavior even in regions of stress and strain space not covered by data from laboratory tests. A disadvantage associated with these models is there relative inflexibility. A given constitutive model has very limited learning capacity through adjustment of model properties. The fundamental shape of the stress-strain relationship does not change.
The constitutive numerical model may be calibrated using laboratory and/or field test data may be used to at least partially define the boundary values. The data may represent boundary value data. A variety of computer codes are available for providing a model through a solution to the boundary value problem. For example, a finite element or a finite difference method can be used to solve equilibrium equations that govern the boundary value problem. Also, a reference library of material models may be used to simulate the constitutive behavior of the soil. This general process as currently known, however, leaves many problems unresolved.
The data obtained from current laboratory and/or field-testing procedures and apparatuses, for example, are often not sufficient as a basis for comprehensive modeling. Field-testing may be performed using devices that penetrate the soil and measure axisymmetric states of stress. These include the Standard Penetration Test (SPT) or the Cone Penetrometer Test (CPT). These devices are generally unable to obtain some data important for soil modeling, such as the soil friction angle. The strain path method is one example of a computational method that has been used before to interpret soil properties around a CPT, an SPT and other in field-testing devices. Although this technique can be used to interpret strains, it is unable to develop the stress-strain relationship unless data such as the soil friction angle is assumed.
Additional problems are presented in the extent of testing required using presently known apparatuses and methods. Soil behavior is highly anisotropic and is difficult to fully characterize using a single test device. Historically, a large number of laboratory tests have been required using a range of test devices to obtain even a limited characterization of the soil properties. Known test devices generally measure only uniform states of stress and strain, and include a triaxial test apparatus, a plane strain apparatus, a hollow cylinder apparatus, a direct shear apparatus, a true triaxial apparatus, and similar devices. It is not uncommon for tests using the devices to number over one hundred in order to obtain a comprehensive data set.
It is also known to utilize observation of soil behavior under actual construction conditions may to verify soil models that have been developed using data from field and/or laboratory tests. If the behavior predicted by the model appears to be inconsistent with field observations, the model may be “tweaked” or otherwise adjusted to better correlate to the observed results. In the prior art, however, these model adjustments have only been made on an ad-hoc basis, with the result that they may be inconsistent and not accurately applied. Also, many models developed using laboratory and/or field-testing do not have the flexibility to be readily adjusted.
These and other problems remain unresolved in the art.